The frequency feature extraction of the signal in oscillation cavity of a self-resonating jet nozzle based on improved HHT method

Flow pressure pulsation in nozzle's oscillation cavity directly reflects the characteristics of self-resonating jet. Effectively extracting the pulsation features in the oscillation is of great significance to study the generation of self-resonating jet. Hilbert-Huang transform(HHT) can be adapted to express the complex nonlinear and non-stationary signals as Hilbert spectrum by empirical mode decomposition(EMD)and HHT, and it can highlight the region characteristic of signals, therefore, it has a good time-frequency aggregation ability. However, HHT has problems of mode mixing and false intrinsic mode functions (IMFs), which make it difficult to obtain the accurate IMFs and precise signal characteristics. Based on this, this research used improved HHT method of ensemble empirical mode decomposition(EEMD)and energy ratiotest, combining with the marginal spectrums of the effective IMFs. Through analyzing of the measured signal in the self-resonating jet nozzle, the result shows that the improved HHT method can more accurately and more clearly extract the nozzle natural vibration frequency and working frequency. © All right reserved.